Moving beyond the physical impervious surface impact and urban habitat fragmentation of Alaska: quantitative human footprint inference from the first large scale 30 m high-resolution Landscape metrics big data quantification in R and the cloud.

IF 2.4 3区 生物学 Q2 MULTIDISCIPLINARY SCIENCES PeerJ Pub Date : 2025-03-24 eCollection Date: 2025-01-01 DOI:10.7717/peerj.18894
Moriz Steiner, Falk Huettmann
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引用次数: 0

Abstract

With increased globalization, man-made climate change, and urbanization, the landscape-embedded within the Anthropocene-becomes increasingly fragmented. With wilderness habitats transitioning and getting lost, globally relevant regions considered 'pristine', such as Alaska, are no exception. Alaska holds 60% of the U.S. National Park system's area and is of national and international importance, considering the U.S. is one of the wealthiest nations on earth. These characteristics tie into densities and quantities of human features, e.g., roads, houses, mines, wind parks, agriculture, trails, etc., that can be summarized as 'impervious surfaces.' Those are physical impacts and actively affecting urban-driven landscape fragmentation. Using the remote sensing data of the National Land Cover Database (NLCD), here we attempt to create the first quantification of this physical human impact on the Alaskan landscape and its fragmentation. We quantified these impacts using the well-established landscape metrics tool 'Fragstats', implemented as the R package "landscapemetrics" in the desktop software and through the interface of a Linux Cloud-computing environment. This workflow allows for the first time to overcome the computational limitations of the conventional Fragstats software within a reasonably quick timeframe. Thereby, we are able to analyze a land area as large as approx. 1,517,733 km2 (state of Alaska) while maintaining a high assessment resolution of 30 m. Based on this traditional methodology, we found that Alaska has a reported physical human impact of c. 0.067%. We additionally overlaid other features that were not included in the input data to highlight the overall true human impact (e.g., roads, trails, airports, governance boundaries in game management and park units, mines, etc.). We found that using remote sensing (human impact layers), Alaska's human impact is considerably underestimated to a meaningless estimate. The state is more seriously fragmented and affected by humans than commonly assumed. Very few areas are truly untouched and display a high patch density with corresponding low mean patch sizes throughout the study area. Instead, the true human impact is likely close to 100% throughout Alaska for several metrics. With these newly created insights, we provide the first state-wide landscape data and inference that are likely of considerable importance for land management entities in the state of Alaska, and for the U.S. National Park systems overall, especially in the changing climate. Likewise, the methodological framework presented here shows an Open Access workflow and can be used as a reference to be reproduced virtually anywhere else on the planet to assess more realistic large-scale landscape metrics. It can also be used to assess human impacts on the landscape for more sustainable landscape stewardship and mitigation in policy.

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超越阿拉斯加的物理不透水地表影响和城市栖息地破碎化:基于R和云的第一次大规模30米高分辨率景观指标大数据量化的定量人类足迹推断。
随着全球化、人为气候变化和城市化的加剧,嵌入人类世的景观变得越来越破碎。随着荒野栖息地的转变和消失,阿拉斯加等被认为是“原始”的全球相关地区也不例外。阿拉斯加拥有美国国家公园系统60%的面积,考虑到美国是地球上最富有的国家之一,它在国内和国际上都具有重要意义。这些特征与人类特征的密度和数量有关,例如道路、房屋、矿山、风力公园、农业、小径等,这些特征可以概括为“不透水表面”。这些都是物理影响,积极影响城市驱动的景观破碎化。利用国家土地覆盖数据库(NLCD)的遥感数据,我们试图首次量化人类对阿拉斯加景观及其破碎化的物理影响。我们使用成熟的景观度量工具“Fragstats”来量化这些影响,该工具在桌面软件中作为R包“景观度量”实现,并通过Linux云计算环境的接口。该工作流程首次克服了传统Fragstats软件在相当短的时间内的计算限制。因此,我们能够分析的陆地面积约为。1,517,733平方公里(阿拉斯加州),同时保持30米的高评估分辨率。基于这种传统的方法,我们发现阿拉斯加的物理人类影响为0.067%。此外,我们还覆盖了输入数据中未包含的其他特征,以突出整体真实的人类影响(例如,道路,小径,机场,游戏管理中的治理边界和公园单位,矿山等)。我们发现,使用遥感(人类影响层),阿拉斯加的人类影响被大大低估到一个毫无意义的估计。这个国家的分裂和受人类影响的程度比人们通常认为的要严重得多。很少有区域是真正未受影响的,并且在整个研究区域显示出高斑块密度和相应的低平均斑块大小。相反,从几个指标来看,整个阿拉斯加的人类影响可能接近100%。通过这些新创造的见解,我们提供了第一个全州范围的景观数据和推断,这可能对阿拉斯加州的土地管理实体以及整个美国国家公园系统具有相当重要的意义,特别是在气候变化的情况下。同样,这里提出的方法框架展示了一个开放获取的工作流程,可以作为参考,在地球上几乎任何其他地方复制,以评估更现实的大规模景观指标。它还可用于评估人类对景观的影响,以便在政策中实现更可持续的景观管理和缓解。
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来源期刊
PeerJ
PeerJ MULTIDISCIPLINARY SCIENCES-
CiteScore
4.70
自引率
3.70%
发文量
1665
审稿时长
10 weeks
期刊介绍: PeerJ is an open access peer-reviewed scientific journal covering research in the biological and medical sciences. At PeerJ, authors take out a lifetime publication plan (for as little as $99) which allows them to publish articles in the journal for free, forever. PeerJ has 5 Nobel Prize Winners on the Board; they have won several industry and media awards; and they are widely recognized as being one of the most interesting recent developments in academic publishing.
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